Requirements
- Up to 9 years of IT experience & 5+ Years on Hadoop and K8s Eco Systems
- Last 3 years of relevant experience in banking/financial services industry
- Demonstrable analytical skills with deep knowledge of Big Data Ecosystem in a Production Support Environment.
- Hands On Experience within the Hadoop Tool Sets Hive, Hue, Spark, Kafka, Kudu, Flink, Ozone, Kafka and Streaming.
- Strong SQL, Python, Java and Unix shell scripting
- Incident, problem, and service Outage management experience is Plus.
- Good Communication and Articulation Skills
- Strong in data engineering concepts and programming
- Experience in building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Experience in supporting data transformation, data structures, metadata, dependency and workload management.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Responsibilities
- Provide operational support and ensure SLI of Applications
- Troubleshoot Batch Issues & root causes to Mitigate Impacts to SLA
- Proactively Identify and Identify opportunities for preventive Maintenance
- Perform Administration & Optimization to achieve of Optimal System Performance
- Conduct review of technical and functional solutions from enhancement/project team to ensure they conform to Established Standards
- Recommend Design and Operational Optimizations
- Respond on time to the queries raised by various business units
- Provide Timely updates (Status, Progress, Issues, Resolutions) to Business Stakeholders
- Work with Project/Enhancement Teams to Review, Transition for Run Team
- Participate in Disaster Recovery and Business Continuity exercises
- Support relevant software/platform/database upgrade for the systems
- Knowledge of Troubleshooting Core Java, Python, Scala spark batch, API and streaming applications
- Support data APIs, data science ML applications running on Kubernetes platform
